A long time ago in a galaxy far,
far away, perky young men and women in Silicon Valley and its overseas
dependencies (Shoreditch, Stockholm and Berlin etc) would proudly display their
technophilia and faith in all things digital on their chests – “tech will save
us” went the strikingly positivist slogan. “Tech” – technique, technology and
process methodology – would always be the answer. Better tech, better answers.
Better tech, better solutions, better lives, better everything. How very Dan
Dare!
Still today we find ourselves as
a culture looking for shiny new things: better “treatments” for medical conditions
(ideally based on something atomic, genetic or smart).
Rather than embrace the human side of the equation, we leap on the promise of a
super smart algorithm to make decisions for us. Rather than work harder in
understanding how our organisation’s communications might work, we’ve bought
the whole “advertising is over” spiel and are left wondering what happened to
sales growth. Rather than deal with the real deficiencies in our service to
customers, let’s automate the feedback channels (and really annoy them while
we’re at it!). And as researchers, rather than think just a little harder about
what it is we’re trying to measure, we default to Big Data, biometrics and
Machine Learning to save us.
This is a mistake. A culturally shaped mistake, for sure, (there’s a very strong mechanistic positivist strand in our culture) but a mistake nonetheless: smarter thinking can lead to better questions and thus to answers, using less data can help us find better answers and fixing the stuff we know is broken (because our customers have long told us about it) will always beat a slightly more precise measure of Brand Equity (whatever we think that is).
It’s not that technology – technique, method, process – won’t help; it’s just that its value always depends on people and how we use it. Technology is all too often a displacement activity.
Tech won’t save us from the future
Nowhere is this most prevalent than in business’ thinking about the future.
Right now, the future is hot, (who needs to think about how we got here or where we are so long as we can focus on what is yet to come). More data, more feedback loops, more oversight, more at risk and more fear of becoming one of those case studies of The Boy/Girl Who Didn’t See It Coming: all of these makes it feel harder than ever before.
It’s always been hard. The
English playwright, Tom Stoppard puts it very well in ‘Arcadia’: “it’s all
very noisy out there. Very hard to spot the tune. Like a piano in the next
room, it’s playing your song but unfortunately it’s out of whack, some of the
strings are missing, and the pianist is tone deaf and drunk – I mean the noise!
Impossible”.
Which is why every human culture
prizes those who can see through the fog of the present into the light – those
who read the meaning in the flight of birds, in the entrails of animal
sacrifice or the pattern in the tealeaves; those who hang about outside
nightclubs or Fashion College Degree Shows to hunt cool kids and cool looks;
those who wade their way through unsigned bands and artists to pick out
Coldplay or Stormzy from the hopefuls.
[As it happens, it seems you
just have to be right once to attain Madam Arcati status as all-seeing crystal
ball cuddler. Just as most of the fashion journalist’s “10 pieces that are
essential for your Spring/Summer wardrobe” will be on the remainder rail by the
end of May, so most gurus’ predictions about consumers are as painfully
misguided as they are pleasantly plausible (we all want the Faith Popcorns of
Marketing to be right – after all we pay them for their visions more than
handsomely and they are so convincing).]
For many in our world of market
research, The Future is now the killer app – our clients no longer hang on our
every word in other subjects but the Future…boy! And if you’re struggling to
justify the investment in all that AI analytics power, what better subject to
throw it at than the Future?
Rethinking the future 1-2-3
Let’s be straight: the future is
generally hard to predict with any confidence, primarily because of the way we
think about it, not because of the tools we use (although they can help when
you sort your thinking out).
I’ve identified three related kinds of problem that really hold back thinking about what lies beyond the mist.
Each of these presents a
significant and real hindrance but together they distort our best efforts at
embracing the future.
First, it’s not just good enough
to predict the future as precisely as we can and all will be well: all
organisations and all individuals are prone to cognitive biases which shapes
what they hear and the decisions they make. The excellent 2017 report by HMG’s
Behavioural Insights Team demonstrated that the same kinds of biases observed
in individual consumers are just as prevalent among those at the top of
(policy) organisations – if not more so. Optimism bias (we are unrealistically
positive about our own and our organisation’s abilities); Confirmation bias
(seeing and hearing only what you want to); Loss Aversion and so on. When
thinking about the future, all organisations are going to ignore what they
don’t want to hear, they will be gung-ho when caution is required and cautious
when change is needed. Whatever the technology you might use to deliver your
prediction.
Second, we have to go beyond
describing the future with ever more precision and instead – following Marx’s
comment on philosophers – to start change it. Too much thinking about the
future is action-lite: it describes the world as we think it might be (“in the
future, we’ll all be eating insects/driving jetcars etc”) but not what the
organisation needs to do about it.
Organisations are often
described as Supertankers and with good reason: they are big, heavy and slow to
turn around. The more successful they are, the harder it is to re-direct them.
They are easily outmanoeuvred by smaller more agile competitors. If we
Futurists want our work to impact on these organisations we have to get them to
think through action, not by providing information.
And finally, straight line
thinking makes The Future a singular thing: a yes, no, right, wrong
thing. When we think about the future (or the past) we tend to describe it in
terms of a single causal line projected from now into the future (or a single
causal line which leads from the past inevitably into the present).
This is another cognitive
limitation to the way we think about the future – a limitation that is probably
part-psychological (the product of our inherited physical mental abilities) and
part-cultural (many other cultures are happy embracing alternative stories
about the past and the future; indeed, many have a much less rigidly linear
view of Past-Present-Future than we do. Hindu beliefs in reincarnation are one
example of this; Australian First People’s continuous time is another). Useful
future thinking needs to find a way to embrace multiples, probabilities and
change over time.
Do or not do?
How might an approach that
embraces these three problems work?
First, we don’t tell people what the future will be like: we create games that
i. help organisations explore multiple new scenarios based on our work and theirs,
ii. to assess the challenge to existing practices, ecosystems and business models and
iii. to identify the key actions the organisation needs to take to start to respond.
Like De Geus and his Scenario
Planning but on steroids: we do this fast and at scale: in half a day a team of
20 executives can create 20-30 scenarios from a judiciously selected and
curated set of prompts (yes, a card-deck) and provide the initial response and
evaluation for all of them.
By exploring and mapping such a
large number of scenarios, our participants are able to see commonalities –
those critical issues that cross scenarios that the organisation needs to act
on immediately (but might otherwise be able to ignore, discounting and
deprioritizing what it doesn’t want to hear).
After this session we/they can
check the estimated probabilities of each scenario and the precise risk it
represents. Indeed, we encourage clients to use the classic probability cone
(Fig 1) to monitor over time how the identified scenarios come closer and drift
further out in probability. This is the place for those fancy AI tools to help
and not before.
However, it is the work by the
team together on multiple scenarios and the actions the organisation needs to
take which makes the real difference. As the 20th Century British painter, Paul
Nash put it, “if you want to understand a landscape, you need to put something
in it”. We help teams understand many different landscapes by putting things in
them.
In effect, the Future comes
closer to the organisation and its executives; it becomes more real and more
than a single place; it’s not some hit or miss theoretical thing; it’s not
accessed by magic or intuition or Machine Learning. It’s something all of us
can think about and act on. The Future is ours – yours and mine.